Background: Chronic kidney disease (CKD) is a fatal disease that ultimately results in kidney failure. The primary threat is the aetiology of CKD. Over the years, researchers have proposed various techniques and methods to detect and diagnose the disease. The conventional method of detecting CKD is the determination of the estimated glomerular filtration rate by measuring creatinine levels in blood or urine. Conventional methods for the detection and classification of CKD are tedious; therefore, several researchers have suggested various alternative methods. Recently, the research community has shown keen interest in developing methods for the early detection of this disease using imaging modalities such as ultrasound, magnetic resonance imaging, and computed tomography.
Discussion: The study aimed to conduct a systematic review of various existing techniques for the detection and classification of different stages of CKD using 2D ultrasound imaging of the kidney. The review was confined to 2D ultrasound images alone, considering the feasibility of implementation even in underdeveloped countries because 2D ultrasound scans are more cost effective than other modalities. The techniques and experimentation in each work were thoroughly studied and discussed in this review.
Conclusion: This review displayed the cutting-age research, challenges, and possibilities of further research and development in the detection and classification of CKD.
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http://dx.doi.org/10.2174/1573405616666200923162600 | DOI Listing |
J Clin Rheumatol
March 2025
Coordinación de Investigación en Salud, Instituto Mexicano del Seguro Social, Puebla, Mexico.
Introduction: Patients with polymyositis and dermatomyositis (PM/DM) are prone to multiple complications that may lead to increased mortality rates. Data about PM/DM mortality in Mexico are lacking.
Objective: The aim of this study was to assess mortality trends in PM/DM in Mexico across 2 decades (2000-2019), overall, by sex, age group, and geographic region.
JMIR Public Health Surveill
March 2025
Nivel - Netherlands Institute for Health Services Research, Otterstraat 118, Utrecht, 3513 CR, The Netherlands, 31 629034652.
Background: Syndromic surveillance systems are crucial for the monitoring of population health and the early detection of emerging health problems. Internationally, there are numerous established systems reporting on different types of data. In the Netherlands, the Nivel syndromic surveillance system provides real-time monitoring on all diseases and symptoms presented in general practice.
View Article and Find Full Text PDFJMIRx Med
March 2025
Stelmith, LLC, 2333 Aberdeen Pl, Carollton, TX, 75007, United States, 1 9459001314.
Background: The increasing integration of artificial intelligence (AI) systems into critical societal sectors has created an urgent demand for robust privacy-preserving methods. Traditional approaches such as differential privacy and homomorphic encryption often struggle to maintain an effective balance between protecting sensitive information and preserving data utility for AI applications. This challenge has become particularly acute as organizations must comply with evolving AI governance frameworks while maintaining the effectiveness of their AI systems.
View Article and Find Full Text PDFBreast cancer is the most prevalent cancer among women and poses a significant global health challenge due to its association with uncontrolled cell proliferation. Artificial intelligence (AI) integration into medical practice has shown promise in boosting diagnosis accuracy and treatment protocol optimisation, thus contributing to improved survival rates globally. This paper presents a comprehensive analysis utilizing the Wisconsin Breast Cancer dataset, comprising data from 569 patients and 30 attributes.
View Article and Find Full Text PDFMicrob Ecol
March 2025
Instituto de Geología, Universidad Nacional Autónoma de México, Ciudad Universitaria, Av. Universidad 3000, Del. Coyoacán, 04510, Ciudad de Mexico, México.
Bacteria and Archaea are microorganisms that play key roles in the biogeochemical transformations that control water quality in freshwater ecosystems, such as in reservoirs. In this study, we characterize the prokaryotic community of a high-relevance tropical eutrophic reservoir using a 16S rRNA gene survey during a low-water level fluctuation period mainly used for storage, associating the distribution of these microorganisms with the hydrogeochemical conditions of the water column. Our findings revealed that diversity and structure of the prokaryotic community exhibited spatio-temporal variations driven by the annual circulation-stratification hydrodynamic cycle and are significantly correlated with the concentrations of dissolved oxygen (DO), soluble reactive phosphorus (SRP), and dissolved inorganic nitrogen (DIN).
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